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Yang Du; Susu Zhang – Journal of Educational and Behavioral Statistics, 2025
Item compromise has long posed challenges in educational measurement, jeopardizing both test validity and test security of continuous tests. Detecting compromised items is therefore crucial to address this concern. The present literature on compromised item detection reveals two notable gaps: First, the majority of existing methods are based upon…
Descriptors: Item Response Theory, Item Analysis, Bayesian Statistics, Educational Assessment
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
Wang, Chun; Xu, Gongjun; Shang, Zhuoran; Kuncel, Nathan – Journal of Educational and Behavioral Statistics, 2018
The modern web-based technology greatly popularizes computer-administered testing, also known as online testing. When these online tests are administered continuously within a certain "testing window," many items are likely to be exposed and compromised, posing a type of test security concern. In addition, if the testing time is limited,…
Descriptors: Computer Assisted Testing, Cheating, Guessing (Tests), Item Response Theory
Evans, William S.; Cavanaugh, Robert; Quique, Yina; Boss, Emily; Starns, Jeffrey J.; Hula, William D. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: The purpose of this study was to develop and pilot a novel treatment framework called "BEARS" (Balancing Effort, Accuracy, and Response Speed). People with aphasia (PWA) have been shown to maladaptively balance speed and accuracy during language tasks. BEARS is designed to train PWA to balance speed-accuracy trade-offs and…
Descriptors: Accuracy, Semantics, Aphasia, Reaction Time
Rudner, Lawrence – Practical Assessment, Research & Evaluation, 2016
In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…
Descriptors: Accuracy, Bayesian Statistics, Regression (Statistics), Probability
Chen, Ping – Journal of Educational and Behavioral Statistics, 2017
Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…
Descriptors: Test Items, Item Response Theory, Test Construction, Adaptive Testing
Markon, Kristian E. – Psychological Methods, 2013
Although advances have improved our ability to describe the measurement precision of a test, it often remains challenging to summarize how well a test is performing overall. Reliability, for example, provides an overall summary of measurement precision, but it is sample-specific and might not reflect the potential usefulness of a test if the…
Descriptors: Measures (Individuals), Psychometrics, Statistical Analysis, Bayesian Statistics
Wang, Chun; Fan, Zhewen; Chang, Hua-Hua; Douglas, Jeffrey A. – Journal of Educational and Behavioral Statistics, 2013
The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the…
Descriptors: Reaction Time, Computer Assisted Testing, Test Items, Accuracy
He, Wei; Reckase, Mark D. – Educational and Psychological Measurement, 2014
For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…
Descriptors: Item Banks, Test Length, Computer Assisted Testing, Adaptive Testing
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries